Cadence Speaking Sessions:
Monday, October 7
10:25am – 11:05am
Intelligent System Design Enabled by Machine Learning in EDA
Michael Shih, Corporate Vice President of Asia Pacific and Japan, Cadence
In the Age of Intelligence, AI and machine learning might usher in radical—arguably unprecedented—changes in the way people live and work. AI has the large potential to contribute to global economic activity. And there’s no debating that machine learning technology is already inside production silicon that spans virtually every technology market segment. Today’s design engineer is at the forefront of this revolution.
A seismic shift may take place in the China chip industry, established fabless companies, system companies with fabless arms, fabless with close partnership with system makers, or any disruptive force with game-changing business models… With the second largest economy and the second largest R&D investment, the only shortage is the engineer force, i.e., seasoned managers and capable engineers. Intelligent System Design enabled by machine learning, a paradigm shift in design methodology, can come to the rescue for the design productivity gap and shortage of experience engineers. Cadence is already using machine learning techniques to produce better, more predictable outcomes for many tasks in the EDA flow. But there are so many more potential areas for improvements. Machine learning can help our customers meet their time-to-market requirements if we can make the design process smarter and reduce the amount of manual intervention necessary. The goal is to allow our tools to suggest solutions to common problems that might otherwise take design teams weeks or months to evaluate.
Cadence is using combinations of statistical models with increasing sophistication in our simulation, verification, analog, power analysis, place-and-route, and modeling tools. And our broad IP offering of DSPs and processors for AI at-the-edge processing and memory IP provides AI capability for consumer devices, while advanced memory interfaces enable machine learning in the cloud and high-performance computing.
Cadence’s machine learning strategy is to pave the next-generation chip design path. Aiming to “build tomorrow’s products today”, Cadence continues to invest in and develop products for this evolving market: Utilizing machine learning/deep learning techniques inside our design tools makes them smarter and faster, as well as increases designer productivity—exponentially.